Description Usage Arguments Details Examples

View source: R/RcppExports.R View source: R/functions.R

Applies a resolution level thresholding technique to a set of wavelet coefficients, embedded in a wavelet coefficient object.

1 | ```
waveletThresh(beta, thresh, shrinkType = "hard")
``` |

`beta` |
A |

`thresh` |
A numeric vector containing the thresholds to be applied to the coefficients at each resolution. |

`shrinkType` |
A character string that specifies which thresholding regime to use. Available choices are the 'hard', 'soft' or 'garrote'. |

Applies one of three specified wavelet thresholding regimes to a `waveletCoef`

object (wavelet
coefficient object created by `multiCoef`

). If `thresh`

is not specified, no thresholding
is applied. The formulae applied for 'hard', 'soft' or
'garrote' are given by,

Hard:

*δ(x) = x 1(|x| > t)*Soft:

*δ(x) = (x - t) 1(x > t) + (x + t) 1(x > -t)*Garrote:

*δ(x) = (x - t^2/x) 1(|x| > t)*

where 1 represents the indicator function and *t > 0* represents the threshold.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | ```
library(mwaved)
# Simulate the multichannel doppler signal.
m <- 3
n <- 2^10
signal <- makeDoppler(n)
# Noise levels per channel
e <- rnorm(m * n)
# Create Gamma blur
shape <- seq(from = 0.5, to = 1, length = m)
scale <- rep(0.25, m)
G <- gammaBlur(n, shape = shape, scale = scale)
# Convolve the signal
X <- blurSignal(signal, G)
# Create error with custom signal to noise ratio
SNR <- c(10, 15, 20)
sigma <- sigmaSNR(X, SNR)
if (requireNamespace("fracdiff", quietly = TRUE)){
alpha <- c(0.75, 0.8, 1)
} else {
alpha <- rep(1, m)
}
E <- multiNoise(n, sigma, alpha)
# Create noisy & blurred multichannel signal
Y <- X + E
# Determine thresholds
thresh <- multiThresh(Y, G)
beta <- multiCoef(Y, G)
betaShrunk <- waveletThresh(beta, thresh)
plot(beta, betaShrunk)
``` |

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